Up to 3 Postdoc Fellowships in Machine Learning

The Department of Computer Science, University of Copenhagen (DIKU) offers up to 3 postdoctoral fellowships in machine learning.

Succesful canddiates are expected to split their time between basic research targeting top-tier publication venues and applied research in collaboration with industrial and academic partners.

The positions are full- time, two-year appointments with competitive salary. We wish our staff to reflect the diversity of society and welcomes applications from all qualified candidates regardless of personal background.

The working language is English, Denmark is among the highest English proficiency index, and the workplace is beautiful Copenhagen which is ranked among the world's most liveable cities.

The positions are open from 22 May 2018 or as soon as possible thereafter.

Terms of employment

The position is covered by the Memorandum on Job Structure for Academic Staff.

Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.

The starting salary is currently up to DKK 419.760 including annual supplement (+ pension up to DKK 71.760). Negotiation for salary supplement is possible.

The application, in English, must be submitted electronically by clicking APPLY NOW below.

Qualifications

The candidates are expected to have a profound background in machine learning. Publications in top-tier venues such sas ICML, NPS, KDD, and CVPR are a requirement.

Please include

Curriculum vita

Diplomas (Master and PhD degree or equivalent)

Complete publication list

Separate reprints of 3 particularly relevant papers

The deadline for applications is 16 April 2018 23:59 GMT +2.

After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Appointments Committee. All applicants are then immediately notified whether their application has been passed for assessment by an expert assessment committee. Selected applicants are notified of the composition of the committee and each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.